Brain Inspired
Paul Middlebrooks
Neuroscience and artificial intelligence work better together. Brain inspired is a celebration and exploration of the ideas driving our progress to understand intelligence. I interview experts about their work at the interface of neuroscience, artificial intelligence, cognitive science, philosophy, psychology, and more: the symbiosis of these overlapping fields, how they inform each other, where they differ, what the past brought us, and what the future brings. Topics include computational neuroscience, supervised machine learning, unsupervised learning, reinforcement learning, deep learning, convolutional and recurrent neural networks, decision-making science, AI agents, backpropagation, credit assignment, neuroengineering, neuromorphics, emergence, philosophy of mind, consciousness, general AI, spiking neural networks, data science, and a lot more. The podcast is not produced for a general audience. Instead, it aims to educate, challenge, inspire, and hopefully entertain those interested in learning more about neuroscience and AI.
Episodes
Mentioned books
11 snips
May 6, 2026 • 1h 42min
BI 237 Ehud Ahissar: Consciousness and Perceptual Dualism
Ehud Ahissar, neuroscientist who leads the Ahissar Lab at the Weizmann Institute, explores perceptual dualism. He contrasts digital brain–brain communication with analog brain–world interaction. He explains how nested sensorimotor loops, attractors, language and active sensing shape these two modes. He also touches on meditation, psychedelics, evolution of language, and implications for AI and society.
23 snips
Apr 22, 2026 • 1h 44min
BI 236 Liset de la Prida: Neurons, Ripples, and Manifolds
Liset de la Prida, director at the Centro de Neurociencias Cajal and leader of a neural circuits lab, explores hippocampal sharp wave ripples and neural manifolds. She explains ripple diversity across states, how ripples broadcast to cortex, and links ripple replay to low-dimensional population trajectories. She also discusses cell-type and deep vs superficial CA1 differences that shape manifold geometry and representation.
44 snips
Apr 8, 2026 • 2h 11min
BI 235 Romain Brette: The Brain, in Theory
Romain Brette, research director in computational and theoretical neuroscience and author of The Brain, in Theory, challenges engineering metaphors for cognition. He critiques information-as-inside-neurons, contrasts process vs substance views, explores paramecium behavior as minimal cognition, and examines anticipation, computation limits, and implications for AI.
29 snips
Mar 25, 2026 • 2h 2min
BI 234 Juan Gallego: The Neural Manifold Manifesto
Juan Gallego, neuroscientist and director of the Neocybernetics Lab, studies neural manifolds, motor control, and restorative neurotechnology. He argues manifolds are real and causally powerful. Conversation covers how manifolds shape learning and cross-species similarities, limits mapping them to psychology, interactions across brain areas, and translating manifold ideas into BCIs and spinal cord prosthetics.
31 snips
Mar 11, 2026 • 1h 40min
BI 233 Tom Griffiths: The Laws of Thought
Tom Griffiths, Princeton cognitive scientist and author of The Laws of Thought, explores how logic, neural networks, and probability form a trio for understanding cognition. He traces historical ideas, contrasts algorithms and implementations, and discusses resource-rationality, amortized inference, and how constraints shape both human minds and modern AI.
26 snips
Feb 25, 2026 • 1h 53min
BI 232 How Should Neuroscience Integrate with Ecological Psychology?
Vicente Raja, a research fellow in ecological psychology and neuroscience; Luis Favela, author and philosopher of the ecological brain; Matthieu de Wit, leader of the Ecological Neuroscience lab. They trace the naturalistic turn in neuroscience, debate whether brain research can honor ecological principles, and explore affordances, ecological information, and practical paths like robotics and multimodal data for true organism–environment science.
35 snips
Feb 11, 2026 • 1h 48min
BI 231 Jaan Aru: Conscious AI? Not Even Close!
Jaan Aru, neuroscientist and co-PI at the Natural and Artificial Intelligence Lab, studies how cellular and circuit-level brain mechanisms relate to consciousness and creativity. He explains why biological details like dendrites and thalamocortical loops matter for consciousness and argues current AI lacks those multi-scale features. He also explores the brain basis of insight and how it links to psychedelic and creative experiences.
51 snips
Jan 28, 2026 • 1h 49min
BI 230 Michael Shadlen: How Thoughts Become Conscious
Michael Shadlen, Columbia neuroscience professor known for decision-making research, offers a compact account of how thoughts shift from nonconscious to conscious. He links persistent neural activity, action-oriented interrogation, reporting and theory-of-mind, and philosophical influences. The conversation touches on neural noise, drift-diffusion dynamics, language’s role in reporting, and whether AI could share this kind of consciousness.
12 snips
Jan 14, 2026 • 1h 41min
BI 229 Tomaso Poggio: Principles of Intelligence and Learning
Tommaso Poggio, a renowned MIT professor and director of the Center for Biological and Computational Learning, dives into the principles of intelligence and learning. He compares the current stage of AI to historical breakthroughs in electricity, advocating for a theory-first approach. Poggio explores how learning can be integrated into existing models, shares insights from early machine learning developments, and discusses the significance of sparse compositionality. He also reflects on the evolving relationship between neuroscience and machine learning, emphasizing the need for theoretical foundation in both fields.
62 snips
Dec 31, 2025 • 1h 58min
BI 228 Alex Maier: Laws of Consciousness
In this enlightening discussion, Alex Maier, an associate professor of psychology at Vanderbilt University and head of the Maier Lab, dives deep into the neuroscience of consciousness. He shares his journey from vision research to exploring integrated information theory, emphasizing the role of mathematics in understanding perception. Alex vividly discusses structuralism and the intriguing concept of mapping subjective experiences to brain mechanisms, all while advocating for open science and collaboration in neuroscience. It's a captivating blend of science and philosophy!
